Leveraging Video Annotations in Video-based e-Learning

Olivier Aubert, Yannick Pri

e and Camila Canellas

University of Nantes, LINA - UMR 6241, Nantes, France

Keywords:

e-Learning, MOOCs, Video Annotation, Pedagogical Processes.

Abstract:

The e-learning community has been producing and using video content for a long time, and in the last years,

the advent of MOOCs greatly relied on video recordings of teacher courses. Video annotations are information

pieces that can be anchored in the temporality of the video so as to sustain various processes ranging from

active reading to rich media editing. In this position paper we study how video annotations can be used in

an e-learning context - especially MOOCs - from the triple point of view of pedagogical processes, current

technical platforms functionalities, and current challenges. Our analysis is that there is still plenty of room for

leveraging video annotations in MOOCs beyond simple active reading, namely live annotation, performance

annotation and annotation for assignment; and that new developments are needed to accompany this evolution.

1 INTRODUCTION

While video material had been used for several

decades as a learning support, the development of

web-based e-learning ﬁrst caused a setback in the

usage of pedagogical videos, due to lack of net-

work bandwidth or standardized formats and soft-

ware. However, video streaming, video hosting and

the dissemination of capture and editing tools have

come along and supported the exponential growth of

video usage on the Web. Again video became an im-

portant component of e-learning setups, through the

OpenCourseWare movement and the recent advent of

Massive Online Open Courses (MOOCs).

Video annotations (section 2) are information

pieces that can be anchored in the temporality of the

video so as to sustain various processes ranging from

active reading to rich media editing (section 3). Our

main interest in this position paper is related to how

video annotations are and can be used in e-learning

context - especially MOOCs - from the triple point

of view of pedagogical processes (section 4), current

technical platforms functionalities (section 5), and

current challenges (section 6). One of the most impor-

tant results of our analysis

is that there is still plenty

of room for leveraging video annotations in MOOCs

beyond simple active reading, namely live annota-

This work has received a French government support

granted to the COMIN Labs excellence laboratory and man-

aged by the National Research Agency in the ”Investing for

the Futures” program ANR-JO-LABX-07-0J.

tion, performance annotation and annotation for as-

signment; and that technological improvements are

needed to accompany this evolution.

2 VIDEO ANNOTATIONS

Active reading is a process where a reader assimilates

and re-uses the object of his reading, as part of his

knowledge work (Waller, 2003). The goals may be

the exploration of a document, its enrichment or its

analysis, for oneself or within a collaborative activ-

ity. Active reading usually relies on annotations, that

add some information to a speciﬁc section or frag-

ment of the target document, and can thereafter be

reused along it for searching, navigating, repurposing,

etc.

The link between the annotation and the origi-

nal document may be more or less explicit, from the

handwritten note in the margin of a book to the note

taken on a notebook while watching a movie (which

will involve more work from the annotator to specify

the targeted information). Two main components of

an annotation are usually considered: its content and

its anchor. The content may take any form, as long as

the underlying support allows it, and can be more or

less structured. Anchoring will depend on the nature

of the annotated document, and will be more or less

explicit and easy to navigate.

We speciﬁcally position ourselves in this article

in the audiovisual context. Video documents present

479

Aubert O., Prié Y. and Canellas C..

Leveraging Video Annotations in Video-based e-Learning.

DOI: 10.5220/0004948604790485

In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 479-485

ISBN: 978-989-758-020-8

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

a number of speciﬁc or more stringent issues. First,

contrary to text content, they do not have any im-

plicit semantics: any active reading must thus be me-

diated through annotations that provide an explicit in-

formation layer along the document. Second, con-

trary to text reading, the reading speed is imposed by

the player. The annotation process then requires some

kind of interruption or interference from the viewing

process, and this conﬂict between the temporality of

the video and that of the annotation process must be

addressed somehow.

Figure 1: Video annotations anchors and content.

A video annotation is composed of data explicitly

associated to a spatiotemporal fragment of a video.

As illustrated in Figure 1, the spatiotemporal anchors

deﬁne at least a timestamp (in the case of duration-

less fragments, specifying a single time in the docu-

ment, e.g. 354), but more generally a begin and an

end timecodes (e.g. 1321 and 1521). They may ad-

ditionally address a speciﬁc static or dynamic zone of

the displayed video (e.g. a rectangle shape that would

follow a player in football video).

Video annotation content data can be of any type.

Textual data is most often used, since it is the easiest

to produce and to consume, but any content (audio,

images, video, key/values...) can as well be associ-

ated. For instance, in a language learning context, the

tutor can take textual notes about a video recording of

a session, and also annotate by recording some spoken

words to indicate the correct pronunciation. Annota-

tions can also be articulated through some structure,

such as a type classiﬁcation: a feature movie analy-

sis could for instance deﬁne different annotation types

like Shot, Sequence or Character appearance (see ﬁg-

ure 1).

3 USING VIDEO ANNOTATIONS

Annotations can be created manually or automati-

cally. Manual creation involves various user inter-

faces, depending on the nature of the task and on the

information that has to be captured (see VideoAnt and

Advene in ﬁgure 2). Annotations may also automati-

cally be created by extracting features from an actual

video document (through speech recognition, or auto-

matic shot detection for example) (Nixon et al., 2013),

or by capturing synchronized information during the

very recording of the document. This last case is used

for instance when recording information about the ac-

tivity of a user: an ergonomics researcher studying the

use of a software can capture a recording of the user

screen while using the software, along with more dis-

crete information capture from the software (button

clicks, ﬁle openings, etc.).

Beyond information retrieval and search, which is

routinely carried out in active reading activities or in

video monitoring systems, video annotations can be

used in a variety of ways, such as enrichment and doc-

ument creation.

Enrichment of the rendering of the video docu-

ment is not new: subtitles can indeed be considered as

video annotations, that are displayed as a caption over

the video. But such overlays can also be graphical, to

attract the attention of the viewer on a speciﬁc visual

element. Video enrichments produced from the anno-

tations can also be placed along the (original) video

player, to produce a navigable table of contents for

instance. Video annotations can also be used to cre-

ate other documents, be it other videos as it is the

case in video summarization (automatic or guided);

or more rich-media documents as an article illustrated

with some fragments (through the annotations) of the

video; or even an annotation-based hypervideo that

permits the navigation from one video to the other.

Eventually, collaborative activities can greatly beneﬁt

from annotations, that here serve as an interpretative

layer between participants.

These different types of uses can be put to use

in different application domains. Video archives

(e.g. TV, surveillance) can propose an enhanced

access to their collections through video annota-

tions, allowing to ﬁnd speciﬁc video fragments. The

Yovisto platform

(Waitelonis and Sack, 2012) of-

fers for example access to video through semantic

annotations, allowing to look for speciﬁc location,

people, events... Sports analysis also greatly re-

lies on video material, which can be used in a re-

ﬂective way by offering the sportsman to view his

own performance, or to analyse the behaviour of

adversaries on recordings of previous competitions.

Many applications such as EliteSportsAnalysis or

MotionView Video Analysis Software offer tools to

annotate and analyse sport performances. Research

on activity in domains such as ergonomics, animal

behaviour, linguistics, etc. also uses annotation soft-

ware, since researchers need to perform a precise

analysis of video recordings. There exist a number

of research tools such as Advene, Anvil or Transana,

as well as commercial offers like Noldus. They all

Underlined terms have an associated URL given in the

Webography annex at the end of the article.

CSEDU2014-6thInternationalConferenceonComputerSupportedEducation

480

Figure 2: On the left, the VideoAnt video online annotation system displays the video with some annotations organised in a

list. On the right, the Advene video annotation tool features several annotation display and creation interfaces: here a timeline

at the bottom and a temporalized note-taking view on the right of the video.

offer annotation capabilities accompanied by various

visualisation and analysis capabilities. Pedagogy is

obviously an important domain for video annotation

practices. First, any matter dealing with videos con-

tent as learning material, such as language or movie

courses (Aubert and Pri

e, 2005; Puig and Sirven,

2007), can beneﬁt from the usage of annotations on

a course support, as in VideoNot.es. Second, discus-

sion about self-reﬂective activities can be enhanced

by annotation-based tools. For instance, VideoTraces

has been used for a long time in dance courses (Cherry

et al., 2003; Bailey et al., 2009) for annotating dance

sessions. More generally, video recordings of learn-

ers presentations or interaction are used to implement

self-reﬂection activities in classrooms (Rich and Han-

naﬁn, 2009), supported by a number of tools such as

VideoTraces, CLAS or MediaNotes.

It appears that a great number of practices have

been experimented in different contexts and applica-

tion domains, from the 1990s VHS based reﬂective

activities to the more recent collaborative and online

video analyses. The experience accumulated on these

tools and practices could fruitfully be incorporated in

e-learning.

4 E-LEARNING PROCESSES

BASED ON VIDEO

ANNOTATIONS

In order to assess in what measure we can leverage the

existing experience in video annotation systems in an

e-learning context, we organize these processes along

four classes of scenarios.

For active reading with annotations, video is a

learning material whose content has to be assimilated

or evaluated. This task is carried out through an it-

erative process, dedicated to the analysis of the au-

diovisual source through its enrichment with annota-

tions and the deﬁnition of appropriate visualisations.

In a learning context, students may annotate the video

material by taking notes, by themselves or collabora-

tively. Conversely, teachers may use the same tech-

niques for evaluating and grading videos produced by

students. And both learners and teachers can engage

into a discussion about a video through annotations.

Live annotation occurs during a live lecture,

which is recorded and annotated at the same time.

Students take notes during the lecture, and reuse these

notes as a basic indexing system when replaying the

recording. Teachers may also let students ask ques-

tions through annotations, and answer them at the end

of the lecture (B

etrancourt et al., 2011).

Performance annotation also implies video as a

trace of a performance, be it recorded in a conven-

tional classroom or during a synchronous online ses-

sion. The recording may already be augmented au-

tomatically by the capture of annotations containing

information about the activity (sent documents, chat

messages, etc). Based on this recorded video and ac-

tivity trace, students may annotate their own perfor-

mance, for self-reﬂection or for sharing an analysis

with their teacher (Rich and Hannaﬁn, 2009). Teach-

ers may as well annotate their own performance in

a self-reﬂective way, to improve their practice (ibid).

Eventually, students may annotate a recorded course

for suggesting improvements or pointing out difﬁcult

sections. The teacher can use that feedback when

preparing the next course or the next version of the

same course (Sadallah et al., 2013).

Eventually, in annotation for assignment, the

video is a material that has to be used to prepare

an assignment (a feature movie, a recording of new

for media analysis, etc). The work may require stu-

dents to analyse some aspects of the video, and pro-

LeveragingVideoAnnotationsinVideo-basede-Learning

481

duce annotations reﬂecting their analysis. The anno-

tations are then later assessed by the teacher (Wong

and Pauline, 2010). Further, the annotations resulting

from the analysis may be reused to produce a new

document, like an abstract or a video collage. At

Columbia University, students use the MediaThread

platform (Bossewitch and Preston, 2011) to produce

critical video composition or critical multimedia es-

says, by combining annotations. The teachers then

assess their productions.

We can identify distinguishing features between

these different classes of scenarios, considering on

the one hand the status of the video, and on the other

hand the actors producing and using the annotations.

The annotated video can be a base learning material,

such as a movie or a documentary to study, or can be

a recording of a lecture (which the students may or

may not have seen live). It can also be the recording

of student contributions. The actors producing and/or

using the annotations can be the students, the teach-

ers, student colleagues or teacher colleagues, or even

the general public.

5 ANNOTATION USES IN

E-LEARNING SYSTEMS

Table 1 provides an overview of the various function-

alities related to video annotation offered by main-

stream MOOC platforms

or more speciﬁcally ded-

icated tools.

From our analysis, it appears ﬁrst that features that

facilitate the comprehension of the discourse - such

as the possibility to adjust the video speed or acti-

vate subtitles and transcriptions - are largely present

in MOOCs. These tools seem to be important in a

multicultural context where subtitles or transcription

are frequently produced in collaboration with student

in the case of translations to other languages. Second,

there is the use of interactive enrichments in MOOC

platforms, usually to have the video stop so that stu-

dents answer a question in order to verify the under-

standing of what had just been explained. Third, if

many MOOC platforms allow adding comments on

video lectures, annotations refering to a part of the

video are only possible via external tools. Fourth, the

dedicated tools we analyzed offer more features re-

Based on courses available in late December 2013.

Some platforms such as Udemy were not considered due

to the fact that they do not have an open access. This table

will be actualized for the ﬁnal version of the paper. A more

detailed version is available on the web and constantly actu-

alized on http://comin-ocw.org/video-annotations/platform-

features/.

garding the annotation process - such as interactive

timelines, export of annotated data, sharing of anno-

tation, etc. - than MOOC platforms.

Thus, most of the solutions presented in Table 1

provide the possibility to develop pedagogical activ-

ities aiming to achieve active reading with annota-

tion from students. Indeed, this is the main use of

such tools by MOOC students, who are seeking a

better understanding of the proposed video material.

Annotation-based active reading can be carried out in-

dividually as well as collaboratively in the majority of

the tools. This last possibility is even more signiﬁ-

cant: as students cannot always rely on having their

doubts/difﬁculties solved by the teacher, collabora-

tion with peers via annotation tools can increase their

understanding along with secondary beneﬁts of devel-

oping cognitive capacities on learning from video, ob-

servational skills and increasing focus and attention.

As far as our other classes of scenarios are con-

cerned, performance annotation was not observed in

the MOOC context although it could lead to an im-

provement of courses as it would be based on facili-

tated self-reﬂection for the teacher or, even better, if

made in collaboration with students. Tasks involving

annotation as assignment were not observed either,

though it is clear that the possibility of critical explo-

ration where students must ﬁnd evidences to support

their thinking could be used within the MOOC con-

text, even so with the use of external annotation tools

and peer evaluation (a well developed practice already

used regarding text assignments).

6 SOME CHALLENGES

It appears that video material and its use in MOOCs

are massive nowadays; nevertheless a more advanced

use of video enrichments and more speciﬁcally of

video annotations is still not a reality. From the

classes of scenarios we described earlier and the

overview of the current situation of e-learning and

MOOC platforms, we would like to put forward

a number of challenges that we think should be

addressed in future versions of e-learning systems,

linked with annotation issues.

Manual Production of Annotations. Manual an-

notation processes raise speciﬁc ergonomic and us-

ability issues, all the more in the video domain where

playing the document may interfere with annotation

entry. The variety of targeted devices like mobile

phones exacerbates these issues. Moreover, as men-

tioned above, annotations are also an ideal vehicle

for collaboration activities around videos, in a syn-

chronous (Nathan et al., 2008) or asynchronous way.

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Table 1: Annotation-related functionalities offered by mainstream MOOC platforms or dedicated tools.

EdX

Coursera

Canvas Network

Khan Academy

Iversity

Open2Study

VideoANT

VideoNot.es

Annotated HTML

Mediathread

YouTube

Matterhorn Player

Visualization

Multilanguage subtitles X

1,2

X X

X X X X

Transcription X X X X X X

Other synchronized enrichments (e.g.

slides)

List of annotations (navigable) X X X X

Timeline with annotations X X

Interactive enrichments on the video or aside

(e.g. embedded questions, alternative endings, hypertext

links to external content)

Editing/sharing features

Comment (about the whole video) X X X X X X

Video markers (single timecode + comment) X

X X X X X

Internal annotation tools (natively on the

platform)

X X X X X X

External annotation tools

(third-party

tools)

X X

Exportation of temporalized data X X

Internal annotations sharing X X

External annotations sharing

X X

Notes: 1. Usually generated automatically with the possibility of correction by the students. 2. Translations into other languages are carried out in collaboration

with students (crowd sourced translation). 3. Synchronized slides. 4. Use of multiple choice embedded question. 5. Video Questions is a new feature available in

beta version. There is also a possibility to choose the ending of a video. 6. Navigation of the video through transcriptions. 7. Usually VideoNot.es, those are the

platforms featured on its website. 8. The use of the tool is promoted on the Coursera wiki page. 9. In most cases, videos on YouTube can be used by the external

tools.

This brings some speciﬁcs issues, notably around the

ergonomics of video co-annotation; as well as privacy

(e.g. the level of shared information must be clearly

displayed and tunable by users).

Semi-automatic Generation of Annotations.

Most video-based e-learning systems use only plain

videos, sometimes fragmented into small indepen-

dent videos, providing only basic features. In or-

der to make these videos more accessible, e-learning

platforms should commonly provide features such as

transcription or chaptering. Some projects such as

TransLectures aim at providing automatic or semi-

automatic transcription of video, so that users may

use the transcription as entry points into the video,

either for querying and ﬁnding speciﬁc fragments, or

as a simple navigation means.

Rich Media and Hypervideos. Beyond the basic

video layout (side to side, overlay) that can be used to

display the video material, annotations can be used to

enrich the video or to produce whole new documents,

such as hypervideos (Chambel et al., 2006) that are

documents combining video and assets originating

from annotations. Challenges here pertain to er-

gonomics, document modelling and (semi-)automatic

production, for instance through an annotation-guided

summarization.

Video Annotations Related Learning Analytics.

With MOOCs, learning analytics have become a ma-

jor concern for all organisations, by necessity - on this

kind of scale, it is important to take informed deci-

sions - and by opportunity - we now have the techno-

logical and processing capacity to capture and analyse

the huge amount of information generated by thou-

sands of learners. The annotation process and the an-

notations themselves offer an additional source of in-

formation for learning analytics at a ﬁner scale, that

could qualify as micro-analytics. Given the impor-

tance of video resources, it is undoubtedly important

to have precise feedback on its reception. This new

source of information could be used for example in

course re-engineering (Sadallah et al., 2013).

Annotation Model and Sharing. Numerous

tools provide video annotation features, and many use

custom data models for storing annotation informa-

tion (Cinelab, Exmeralda). However, standardization

efforts are underway to deﬁne more interoperable and

generic annotation models, able to encompass var-

ious annotation practices on different source docu-

ments and to integrate well with the current seman-

tic web efforts (OpenAnnotation). Let us remark that

some universities, mainly in the US, are strongly com-

mitted to pushing forward and generalizing annota-

LeveragingVideoAnnotationsinVideo-basede-Learning

483

tion practices among students and faculty members,

building annotation ecosystems: Columbia (Bosse-

witch and Preston, 2011), Stanford (Pea et al., 2004)

and Harvard.

All these challenges share common concerns.

First, mobile phones and tablets have become impor-

tant platforms for consulting various resources, and

among them, pedagogical resources. It is important to

propose the most complete experience on annotation-

enhanced e-learning platforms on all devices, and es-

pecially on mobile ones, which have important con-

straints in terms of display size and general capacity.

Second, copyright and licensing issues are even more

stringent, since they concern not only the video doc-

ument (which has to be shareable to allow collabora-

tive work), but also the produced annotations. Clear

licenses for this additional data should be speciﬁed,

hopefully with a bias towards openness and reuse.

Eventually, the question of accessibility - mainly for

sensory deﬁciencies - has to be considered as video

annotations are clearly a means to provide a better

level of accessibility to video content (Encelle et al.,

2011).

We have proposed four classes of scenarios il-

lustrating how video annotations can be used in e-

learning contexts. To evaluate in what measure these

scenarios are feasible or already present, we have re-

viewed a number of e-learning platforms (focusing on

MOOCs) and tools, in order to identify existing anno-

tation features. It appears that if some support already

exists, there is still plenty of room to efﬁciently imple-

ment the scenarios that go beyond simple active read-

ing, and a number of challenges related to video an-

notation still remain. These challenges should be ad-

dressed in future versions of e-learning systems, and

we will tackle some of them in our future work on the

COCo platform

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A WEBOGRAPHY

You will ﬁnd here the URLs referenced in the article, in alphabetical order. Due to editing limitations,

they could not be included as hyperlinks in this version. The version of the article on the author’s website

http://www.comin-ocw.org/ has them properly hyperlinked.

Advene: http://www.advene.org/

Annotated HTML: http://www.stanford.edu/group/ruralwest/cgi-bin/drupal/content/building-annotated-video-

player-html

Anvil: http://www.anvil-software.de/

CLAS: http://isit.arts.ubc.ca/support/clas/

Canvas Network: https://www.canvas.net/

Cinelab: http://advene.org/cinelab/

Cominlabs Open Courseware: http://comin-ocw.org/

Coursera wiki page: https://share.coursera.org/wiki/index.php/Third-party Tools

Coursera: https://www.coursera.org/

EdX: https://www.edx.org/

EliteSportsAnalysis: http://www.elitesportsanalysis.com/

Exmeralda: http://www.exmeralda.org/

Harvard: http://annotations.harvard.edu/

Iversity: https://www.iversity.com/

Khan Academy: https://www.khanacademy.org/

Matterhorn Player: http://opencast.org/matterhorn/feature-tour/

MediaNotes: http://www.cali.org/medianotes

Mediathread: http://mediathread.ccnmtl.columbia.edu/

MotionView Video: http://www.allsportsystems.com/

Noldus: http://www.noldus.com/

Open2Study: https://www.open2study.com/

OpenAnnotation: http://www.w3.org/community/openannotation/

Transana: http://www.transana.org/

Translectures: http://www.translectures.eu/

VideoANT: https://ant2.cehd.umn.edu/

VideoNot.es: http://www.videonot.es/

VideoTraces: http://depts.washington.edu/pettt/projects/videotraces.html

YouTube: http://www.youtube.com/

Yovisto platform: http://www.yovisto.com/

LeveragingVideoAnnotationsinVideo-basede-Learning

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